Software applications for large-scale data analysis and visualization have become essential tools for achieving business objectives in many industries. Such applications are generally used to quickly process large quantities of data to enable the data to be visualized or searched to find key insights, patterns, and important details about the data itself. In the oil and gas industry, such applications may be used to simulate natural fracture networks in unconventional petroleum reservoirs in order to gain a better understanding of the reservoir's physical composition, as well as its economic potential for hydrocarbon exploration and production. The computer models may be generated based on, for example, seismic data representative of the subsurface geological features including, but not limited to, structural unconformities, faults, and folds within different stratigraphic layers of the reservoir formation. In addition to fracture modeling, the computer models may be used by petroleum engineers and geoscientists to visualize two-dimensional (2D), three-dimensional (3D), or four-dimensional (4D) representations of particular stratigraphic features of interest and to simulate the flow of petroleum or other fluids within the reservoir. However, conventional fracture network simulations require a large amount of memory in order to store the mesh data, especially when the triangle meshes are small. Such memory requirements can easily stress or exceed RAM capacity, often effecting overall performance of the system or even initiating a system failure.